https://ogma.newcastle.edu.au/vital/access/ /manager/Index ${session.getAttribute("locale")} 5 https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:34119 -4) with schizophrenia polygenic risk scores explaining up to 0.12% of the variance in ALS (P=8.4 × 10^-7). A modest increase in comorbidity of ALS and schizophrenia is expected given these findings (odds ratio 1.08-1.26) but this would require very large studies to observe epidemiologically. We identify five potential novel ALS-associated loci using conditional false discovery rate analysis. It is likely that shared neurobiological mechanisms between these two disorders will engender novel hypotheses in future preclinical and clinical studies.]]> Wed 04 Sep 2019 09:40:14 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:41878 Tue 16 Aug 2022 10:04:26 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:33388 Tue 03 Sep 2019 17:54:11 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:50043 Thu 29 Jun 2023 14:38:49 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:21465 DRD2 and several genes involved in glutamatergic neurotransmission highlight molecules of known and potential therapeutic relevance to schizophrenia, and are consistent with leading pathophysiological hypotheses. Independent of genes expressed in brain, associations were enriched among genes expressed in tissues that have important roles in immunity, providing support for the speculated link between the immune system and schizophrenia.]]> Sat 24 Mar 2018 07:52:31 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:21040 Sat 24 Mar 2018 07:50:35 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:25812 postmortem brain tissue, and later in studies of peripheral blood. The collective body of schizophrenia microarray literature contains apparent inconsistencies between studies, with failures to replicate top hits, in part due to small sample sizes, cohort-specific effects, differences in array types, and other confounders. In an attempt to summarize existing studies of schizophrenia cases and non-related comparison subjects, we performed two mega-analyses of a combined set of microarray data from postmortem prefrontal cortices (n = 315) and from ex-vivo blood tissues (n = 578). We adjusted regression models per gene to remove non-significant covariates, providing best-estimates of transcripts dysregulated in schizophrenia. We also examined dysregulation of functionally related gene sets and gene co-expression modules, and assessed enrichment of cell types and genetic risk factors. The identities of the most significantly dysregulated genes were largely distinct for each tissue, but the findings indicated common emergent biological functions (e.g. immunity) and regulatory factors (e.g., predicted targets of transcription factors and miRNA species across tissues). Our network-based analyses converged upon similar patterns of heightened innate immune gene expression in both brain and blood in schizophrenia. We also constructed generalizable machine-learning classifiers using the blood-based microarray data. Our study provides an informative atlas for future pathophysiologic and biomarker studies of schizophrenia.]]> Sat 24 Mar 2018 07:34:35 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:20198 Mon 22 Jun 2020 13:17:12 AEST ]]>